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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-tiny-patch4-window8-256 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: swinv2-tiny-patch4-window8-256-finetuned-PE |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8720186154741129 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# swinv2-tiny-patch4-window8-256-finetuned-PE |
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This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3083 |
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- Accuracy: 0.8720 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00025 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 1024 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.92 | 9 | 0.6391 | 0.6690 | |
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| 0.6873 | 1.95 | 19 | 0.5293 | 0.7376 | |
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| 0.6233 | 2.97 | 29 | 0.6385 | 0.6853 | |
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| 0.5976 | 4.0 | 39 | 0.4447 | 0.7970 | |
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| 0.5552 | 4.92 | 48 | 0.4029 | 0.8266 | |
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| 0.552 | 5.95 | 58 | 0.3675 | 0.8429 | |
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| 0.5055 | 6.97 | 68 | 0.3409 | 0.8581 | |
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| 0.4816 | 8.0 | 78 | 0.3322 | 0.8615 | |
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| 0.455 | 8.92 | 87 | 0.3166 | 0.8639 | |
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| 0.4428 | 9.95 | 97 | 0.3100 | 0.8662 | |
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| 0.4398 | 10.97 | 107 | 0.3713 | 0.8365 | |
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| 0.4318 | 12.0 | 117 | 0.4019 | 0.8284 | |
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| 0.4431 | 12.92 | 126 | 0.3074 | 0.8714 | |
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| 0.4437 | 13.95 | 136 | 0.3156 | 0.8656 | |
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| 0.4482 | 14.97 | 146 | 0.3516 | 0.8476 | |
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| 0.4353 | 16.0 | 156 | 0.3162 | 0.8598 | |
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| 0.4218 | 16.92 | 165 | 0.3018 | 0.8685 | |
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| 0.4111 | 17.95 | 175 | 0.3143 | 0.8650 | |
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| 0.4224 | 18.97 | 185 | 0.3146 | 0.8592 | |
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| 0.4114 | 20.0 | 195 | 0.3097 | 0.8691 | |
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| 0.4103 | 20.92 | 204 | 0.3038 | 0.8703 | |
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| 0.3989 | 21.95 | 214 | 0.2893 | 0.8796 | |
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| 0.3908 | 22.97 | 224 | 0.2956 | 0.8755 | |
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| 0.3923 | 24.0 | 234 | 0.3041 | 0.8685 | |
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| 0.3842 | 24.92 | 243 | 0.2876 | 0.8749 | |
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| 0.3808 | 25.95 | 253 | 0.2907 | 0.8767 | |
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| 0.382 | 26.97 | 263 | 0.3018 | 0.8738 | |
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| 0.3816 | 28.0 | 273 | 0.2812 | 0.8825 | |
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| 0.379 | 28.92 | 282 | 0.2960 | 0.8633 | |
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| 0.3858 | 29.95 | 292 | 0.2960 | 0.8743 | |
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| 0.3546 | 30.97 | 302 | 0.2850 | 0.8807 | |
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| 0.3656 | 32.0 | 312 | 0.2905 | 0.8784 | |
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| 0.3707 | 32.92 | 321 | 0.2926 | 0.8743 | |
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| 0.3651 | 33.95 | 331 | 0.2941 | 0.8796 | |
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| 0.3584 | 34.97 | 341 | 0.3133 | 0.8615 | |
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| 0.36 | 36.0 | 351 | 0.3181 | 0.8679 | |
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| 0.3496 | 36.92 | 360 | 0.3036 | 0.8685 | |
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| 0.3458 | 37.95 | 370 | 0.2939 | 0.8732 | |
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| 0.3431 | 38.97 | 380 | 0.3062 | 0.8703 | |
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| 0.3512 | 40.0 | 390 | 0.2914 | 0.8755 | |
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| 0.3512 | 40.92 | 399 | 0.3164 | 0.8674 | |
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| 0.3403 | 41.95 | 409 | 0.3063 | 0.8679 | |
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| 0.3423 | 42.97 | 419 | 0.3018 | 0.8720 | |
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| 0.3312 | 44.0 | 429 | 0.3094 | 0.8697 | |
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| 0.3365 | 44.92 | 438 | 0.3062 | 0.8755 | |
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| 0.3319 | 45.95 | 448 | 0.3081 | 0.8720 | |
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| 0.3409 | 46.15 | 450 | 0.3083 | 0.8720 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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